Search Results for author: Bolette Pedersen

Found 13 papers, 2 papers with code

ELEXIS - a European infrastructure fostering cooperation and information exchange among lexicographical research communities

no code implementations GWC 2018 Bolette Pedersen, John McCrae, Carole Tiberius, Simon Krek

The paper describes objectives, concept and methodology for ELEXIS, a European infrastructure fostering cooperation and information exchange among lexicographical research communities.

Towards a principled approach to sense clustering – a case study of wordnet and dictionary senses in Danish

no code implementations GWC 2018 Bolette Pedersen, Manex Agirrezabal, Sanni Nimb, Ida Olsen, Sussi Olsen

Our aim is to develop principled methods for sense clustering which can make existing lexical resources practically useful in NLP – not too fine-grained to be operational and yet finegrained enough to be worth the trouble.

An empirically grounded expansion of the supersense inventory

1 code implementation GWC 2016 Hector Martinez Alonso, Anders Johannsen, Sanni Nimb, Sussi Olsen, Bolette Pedersen

We cover the expansion of the already-established supernsense inventory for nouns and verbs, the addition of coarse supersenses for adjectives in absence of a canonical supersense inventory, and super-senses for verbal satellites.

DanNet2: Extending the coverage of adjectives in DanNet based on thesaurus data (project presentation)

no code implementations EACL (GWC) 2021 Sanni Nimb, Bolette Pedersen, Sussi Olsen

We describe the methodology and initial work of semi-automatically transferring adjectives from the Danish Thesaurus to the wordnet with the aim of easily enlarging the coverage from 3, 000 to approx.

Towards a Gold Standard for Evaluating Danish Word Embeddings

no code implementations LREC 2020 Nina Schneidermann, Rasmus Hvingelby, Bolette Pedersen

The goal standard is applied for evaluating the {``}goodness{''} of six existing word embedding models for Danish, and it is discussed how a relatively low correlation can be explained by the fact that semantic similarity is substantially more challenging to model than relatedness, and that there seems to be a need for future human judgments to measure similarity in full context and along more than a single spectrum.

Semantic Similarity Semantic Textual Similarity +1

World Class Language Technology - Developing a Language Technology Strategy for Danish

no code implementations LREC 2020 Sabine Kirchmeier, Bolette Pedersen, Sanni Nimb, Philip Diderichsen, Peter Juel Henrichsen

Although Denmark is one of the most digitized countries in Europe, no coordinated efforts have been made in recent years to support the Danish language with regard to language technology and artificial intelligence.

The SemDaX Corpus ― Sense Annotations with Scalable Sense Inventories

no code implementations LREC 2016 Bolette Pedersen, Anna Braasch, Anders Johannsen, H{\'e}ctor Mart{\'\i}nez Alonso, Sanni Nimb, Sussi Olsen, Anders S{\o}gaard, Nicolai Hartvig S{\o}rensen

The aim of the developed corpus is twofold: i) to assess the reliability of the different sense annotation schemes for Danish measured by qualitative analyses and annotation agreement scores, and ii) to serve as training and test data for machine learning algorithms with the practical purpose of developing sense taggers for Danish.

CLARA: A New Generation of Researchers in Common Language Resources and Their Applications

no code implementations LREC 2014 Koenraad De Smedt, Erhard Hinrichs, Detmar Meurers, Inguna Skadi{\c{n}}a, Bolette Pedersen, Costanza Navarretta, N{\'u}ria Bel, Krister Lind{\'e}n, Mark{\'e}ta Lopatkov{\'a}, Jan Haji{\v{c}}, Gisle Andersen, Przemyslaw Lenkiewicz

CLARA (Common Language Resources and Their Applications) is a Marie Curie Initial Training Network which ran from 2009 until 2014 with the aim of providing researcher training in crucial areas related to language resources and infrastructure.

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